AI is becoming a critical strategic tool in manufacturing, enabling organizations to establish new points of differentiation in a rapidly evolving technological environment.
In the defense industry, that strategic differentiation carries enormous weight, given that lives are at stake. Across the military enterprise, AI tools are poised to help deliver speed, precision, and reliability—factors that directly translate into successful mission outcomes.
AI strengthens processes, reduces risk, and accelerates the delivery of new capabilities to the warfighter by helping modernize design, production, and sustainment practices. Equipment and know-how reach the field faster, enabling deployed forces to evolve tactics, techniques, and procedures over shorter cycles.
For program managers, AI’s use in military manufacturing serves as a turning point in continued efforts to build and maintain operational readiness, which is essential due to increasing competition and the emergence of new and evolving threats.
AI-enabled modeling and simulation processes are leading the transformation of military manufacturing. They enable engineers and program managers to create virtual prototypes of equipment so they can explore performance parameters, try new designs and configurations, test potential points of failure, and factor in real-time, data-informed feedback.
Known as “digital twins,” these prototypes have enormous advantages in the form of lower costs, greater flexibility, and improved collaboration throughout the military manufacturing process. Virtual models reduce the time and money spent on producing and testing physical prototypes. Advanced predictive analytics replaces what used to be guesswork with real-time, data-informed predictions of how a certain process or piece of equipment will perform.
The efficiencies gained through generative design and digital twins cascade across the battlefield. They help reduce friction at various points along the acquisition and sustainment process so new systems can get to the field more quickly.
This also provides indirect benefits in terms of how the military operates. With greater confidence in the reliability of deployed systems, commanders can devise more aggressive plans without worrying about untimely breakdowns or outpacing supply channels.
The US Air Force has used generative design and prototyping in developing the new F-47 sixth-generation fighter aircraft, part of the Next-Generation Air Dominance program aimed at creating successors to the F-22 and F-35. The Pentagon awarded Boeing a contract for engineering and manufacturing for the new platform in March 2025 and later confirmed that the first model is already in production.
Notably, the F-47 is being developed using advanced digital engineering techniques that have rapidly accelerated design choices. According to Air and Space Forces Magazine: “The F-47 was also designed with a ‘built to adapt’ mindset, [Former Air Force Chief of Staff David W. Allvin] said, a likely reference to digital design and an open-systems architecture that will allow frequent changeouts of software, sensors and other mission gear. He also said the fighter will ‘take significantly less manpower and infrastructure to deploy,’ suggesting a reduced dependence on ground equipment and more maintenance-friendly components.
AI also provides military manufacturers with tools to help make the production process more predictable and reliable by enabling new quality controls for the factory line.
Integrating machine vision and combining it with AI and predictive analytics enables the detection of defects before they are embedded in the product and shipped to customers. This process serves as an early-warning system that reduces the risk of untimely failures when lives are on the line. In the long term, it also saves time and money, cutting down the need for repeated manufacturing cycles.
Overall, AI and machine learning are confidence-builders for warfighters and their commanders. They supercharge the ability to catch problems at a speed and level that humans can’t possibly provide.
Improved quality control benefits the availability of platforms across the sustainment chains. Commanders don’t have to worry about not having the necessary assets, as these capabilities help keep them in mission-ready condition for extended periods.
They also elevate quality control to an almost microscopic level. For example, Lockheed Martin has developed the Autonomous AI-enabled InspectoR system, or AAIR, that allows for the close inspection of surfaces on commercial and military aircraft. The system combines AI algorithms and machine vision to help identify potentially serious issues, such as corrosion. The AAIR system is portable, a key element for military personnel who often operate in remote and dangerous environments. Lockheed is piloting the technology at one of its factories to inspect C-130 aircraft as they exit the production facility, which enables a “streamlined inspection process [and] reduced inspection time and costs, all while maintaining the highest quality standards.”
Taken together, these AI technologies alter the rhythms of a campaign, enabling warfighters to focus more on execution rather than mechanics while reducing costs and freeing resources that might have been allocated to maintenance for more mission-related needs.
AI can also become a force multiplier in driving factory efficiency. The key is data fusion. AI integrates sensor, machine, and production data into a single operational picture, enabling managers to identify problems and take immediate action.
One example of how this can work is through predictive logistics and maintenance. Algorithms forecast component wear, machine downtime, and supply chain disruptions before they occur, thus reducing costly production pauses.
The Army has implemented predictive maintenance programs for a while now, and they are yielding increasing benefits in terms of cost and efficiency. According to Defense News, "[i]n one instance, a UH-60 Black Hawk was experiencing some abnormal tail rotor vibrations. Using predictive maintenance capabilities, the Army determined a gearbox was failing." It was later estimated that the aircraft was just hours away from a catastrophic failure.
AI tools can also help with load management across production lines. It can facilitate adaptive scheduling by dynamically reallocating resources—machines, personnel, and materials—to ensure that production keeps pace with urgent demands.
The ability to spot anomalies can extend to providing cyber protection for manufacturing operations. The tool can detect irregularities in data flow that suggest intrusions into systems, triggering alarms that can prompt an emergency response.
Real-time adaptability ensures that the defense industrial base can surge production during crises and rapidly scale to equip warfighters in high-intensity operations.
By accelerating design cycles, ensuring the reliability of mission-critical platforms, and driving real-time adaptability across operations, AI empowers DoD program managers and contracting officers to deliver capabilities that align with mission urgency. The result is greater efficiency and a more responsive defense industrial base, one that equips US forces more quickly, sustains them longer, and adapts at the same pace as the battlefield.
Sumaria Systems has over forty years of experience providing innovative engineering services and solutions. Its team stands ready to help you leverage the benefits of AI in cutting-edge ways to drive efficiency in your program.
Digital twins and AI bring real-time foresight and control into defense manufacturing. Whether building new systems or sustaining legacy platforms, these technologies empower DoD leaders to reduce cost, mitigate risk, and ensure production resilience at scale. Contact us for help with the strategic integration of advanced technologies and methods to streamline and optimize the development, maintenance, and operation of systems and infrastructures.